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Step-based tutoring consists in breaking down complicated problem-solving procedures into individual steps whose inputs can be immediately evaluated to promote effective student learning. Here, recent progress on the extension of a step-based tutoring for linear circuit analysis to cover new topics requiring complex, multi-step solution procedures is described. These topics include first and second-order transient problems solved using classical differential equation approaches. Students use an interactive circuit editor to modify the circuit appropriately for each step of the analysis, followed by writing and solving equations using methods of their choice as appropriate. Initial work on Laplace transform-based circuit analysis is also discussed. Detailed feedback is supplied at each step along with fully worked examples, supporting introductory multiple-choice tutorials and YouTube videos, and a full record of the student's work is created in a PDF document for later study and review. Further, results of a comprehensive independent evaluation involving both quantitative and qualitative analysis and users across four participating institutions are discussed. Overall, students had very favorable experiences using the step-based system across Fall 2020 and Spring 2021. At least 48% of students in the Fall 2020 semester and 60% of students in the Spring 2021 semester agreed or strongly agreed with all survey questions about positive features of the system. Those who had used the step-based system and the commercial MasteringEngineering system preferred the former by 69% to 12% margins in surveys. Instructors were further surveyed and 86% would recommend the system to others. 

Step-based tutoring consists in breaking down complicated problem-solving procedures into individual steps whose inputs can be immediately evaluated to promote effective student learning. Here, recent progress on the extension of a step-based tutoring for linear circuit analysis to cover new topics requiring complex, multi-step solution procedures is described. These topics include first and second-order transient problems solved using classical differential equation approaches. Students use an interactive circuit editor to modify the circuit appropriately for each step of the analysis, followed by writing and solving equations using methods of their choice as appropriate. Initial work on Laplace transform-based circuit analysis is also discussed. Detailed feedback is supplied at each step along with fully worked examples, supporting introductory multiple-choice tutorials and YouTube videos, and a full record of the student's work is created in a PDF document for later study and review. Further, results of a comprehensive independent evaluation involving both quantitative and qualitative analysis and users across four participating institutions are discussed. Overall, students had very favorable experiences using the step-based system across Fall 2020 and Spring 2021. At least 48% of students in the Fall 2020 semester and 60% of students in the Spring 2021 semester agreed or strongly agreed with all survey questions about positive features of the system. Those who had used the step-based system and the commercial MasteringEngineering system preferred the former by 69% to 12% margins in surveys. Instructors were further surveyed and 86% would recommend the system to others. 

Earth system models are valuable tools for understanding how the Arctic snow‐ice system and the feedbacks therein may respond to a warming climate. In this analysis, we investigate snow on Arctic sea ice to better understand how snow conditions may change under different forcing scenarios. First, we use in situ, airborne, and satellite observations to assess the realism of the Community Earth System Model (CESM) in simulating snow on Arctic sea ice. CESM versions one and two are evaluated, with V1 being the Large Ensemble experiment (CESM1‐LE) and V2 being configured with low‐ and high‐top atmospheric components. The assessment shows CESM2 underestimates snow depth and produces overly uniform snow distributions, whereas CESM1‐LE produces a highly variable, excessively‐thick snow cover. Observations indicate that snow in CESM2 accumulates too slowly in autumn, too quickly in winter‐spring, and melts too soon and rapidly in late spring. The 1950–2050 trends in annual mean snow depths are markedly smaller in CESM2 (−0.8 cm decade⁻¹) than in CESM1‐LE (−3.6 cm decade⁻¹) due to CESM2 having less snow overall. A perennial, thick sea‐ice cover, cool summers, and excessive summer snowfall facilitate a thicker, longer‐lasting snow cover in CESM1‐LE. Under the SSP5‐8.5 forcing scenario, CESM2 shows that, compared to present‐day, snow on Arctic sea ice will: (1) undergo enhanced, earlier spring melt, (2) accumulate less in summer‐autumn, (3) sublimate more, and (4) facilitate marginally more snow‐ice formation. CESM2 also reveals that summers with snow‐free ice can occur ∼30–60 years before an ice‐free central Arctic, which may promote faster sea‐ice melt.

 

We analyze two preindustrial experiments from the Community Earth System Model version 2 to characterize the impact of sea ice physics on differences in coastal sea ice production around Antarctica and the resulting impact on the ocean and atmosphere. The experiment in which sea ice is a more realistic “mushy” mixture of solid ice and brine has a substantial increase in coastal sea ice frazil and snow ice production that is accompanied by decreasing bottom ice growth and increasing bottom melt. The more realistic “mushy” physics leads to an increase in water mass formation at denser water classes due primarily to surface ice processes. As a result, the subsurface ocean is denser, saltier, and there is an increase in Antarctic Bottom Water formation of0.5 Sv. For the atmosphere, “mushy” ice physics leads to decreased turbulent heat flux and low level cloud cover near the Antarctic coast.

 

The formation of novel and disappeared climates between the last glacial maximum (LGM) and the present is important to consider to understand the expansion and contraction of species niches and distributions, as well as the formation and loss of communities and ecological interactions over time. Our choice in climate data resolution has the potential to complicate predictions of the ecological impacts of climate change, since climate varies from local to global scales and this spatial variation is reflected in climate data. To address this issue, we downscaled LGM and modern (1975–2005) 30‐year averaged climate data to 60‐m resolution for the entire state of Alaska for 10 different climate variables, and then upsampled each variable to coarser resolutions (60 m to 12 km). We modeled the distributions of novel and disappeared climates to evaluate the locations and fractional area of novel and disappeared climates for each of our climate variables and resolutions. Generally, novel and disappeared climates were located in southern Alaska, although there were cases where some disappeared climates existed within coastal and interior Alaska. Climate resolution affected the fractional area of novel and disappeared climates in three patterns: As the spatial resolution of climate became coarser, the fractional area of novel and disappeared climates (a) increased, (b) decreased, or (c) had no explainable relationship. Overall, we found the use of coarser climate data increased the fractional area of novel and disappeared climates due to decreased environmental variability and removal of climate extremes. Our results reinforce the importance of downscaling coarse climate data and suggest that studies analyzing the effects of climate change on ecosystems may overestimate or underestimate their conclusions when utilizing coarse climate data.

 

We examine the response of the Community Earth System Model Versions 1 and 2 (CESM1 and CESM2) to abrupt quadrupling of atmospheric CO₂concentrations (4xCO2) and to 1% annually increasing CO₂concentrations (1%CO2). Different estimates of equilibrium climate sensitivity (ECS) for CESM1 and CESM2 are presented. All estimates show that the sensitivity of CESM2 has increased by 1.5 K or more over that of CESM1. At the same time the transient climate response (TCR) of CESM1 and CESM2 derived from 1%CO2 experiments has not changed significantly—2.1 K in CESM1 and 2.0 K in CESM2. Increased initial forcing as well as stronger shortwave radiation feedbacks are responsible for the increase in ECS seen in CESM2. A decomposition of regional radiation feedbacks and their contribution to global feedbacks shows that the Southern Ocean plays a key role in the overall behavior of 4xCO2 experiments, accounting for about 50% of the total shortwave feedback in both CESM1 and CESM2. The Southern Ocean is also responsible for around half of the increase in shortwave feedback between CESM1 and CESM2, with a comparable contribution arising over tropical ocean. Experiments using a thermodynamic slab‐ocean model (SOM) yield estimates of ECS that are in remarkable agreement with those from fully coupled Earth system model (ESM) experiments for the same level of CO₂increase. Finally, we show that the similarity of TCR in CESM1 and CESM2 masks significant regional differences in warming that occur in the 1%CO2 experiments for each model.

 

The Community Earth System Model Version 2 (CESM2) has an equilibrium climate sensitivity (ECS) of 5.3 K. ECS is an emergent property of both climate feedbacks and aerosol forcing. The increase in ECS over the previous version (CESM1) is the result of cloud feedbacks. Interim versions of CESM2 had a land model that damped ECS. Part of the ECS change results from evolving the model configuration to reproduce the long‐term trend of global and regional surface temperature over the twentieth century in response to climate forcings. Changes made to reduce sensitivity to aerosols also impacted cloud feedbacks, which significantly influence ECS. CESM2 simulations compare very well to observations of present climate. It is critical to understand whether the high ECS, outside the best estimate range of 1.5–4.5 K, is plausible.

 

Because of the pervasive role of water in the Earth system, the relative abundances of stable isotopologues of water are valuable for understanding atmospheric, oceanic, and biospheric processes, and for interpreting paleoclimate proxy reconstructions. Isotopologues are transported by both large‐scale and turbulent flows, and the ratio of heavy to light isotopologues changes due to fractionation that can accompany condensation and evaporation processes. Correctly predicting the isotopic distributions requires resolving the relationships between large‐scale ocean and atmospheric circulation and smaller‐scale hydrological processes, which can be accomplished within a coupled climate modeling framework. Here we present the water isotope‐enabled version of the Community Earth System Model version 1 (iCESM1), which simulates global variations in water isotopic ratios in the atmosphere, land, ocean, and sea ice. In a transient Last Millennium simulation covering the 850–2005 period, iCESM1 correctly captures the late‐twentieth‐century structure of δ¹⁸O and δD over the global oceans, with more limited accuracy over land. The relationship between salinity and seawater δ¹⁸O is also well represented over the observational period, including interbasin variations. We illustrate the utility of coupled, isotope‐enabled simulations using both Last Millennium simulations and freshwater hosing experiments with iCESM1. Closing the isotopic mass balance between all components of the coupled model provides new confidence in the underlying depiction of the water cycle in CESM, while also highlighting areas where the underlying hydrologic balance can be improved. The iCESM1 is poised to be a vital community resource for ongoing model development with both modern and paleoclimate applications.

 

An overview of the Community Earth System Model Version 2 (CESM2) is provided, including a discussion of the challenges encountered during its development and how they were addressed. In addition, an evaluation of a pair of CESM2 long preindustrial control and historical ensemble simulations is presented. These simulations were performed using the nominal 1° horizontal resolution configuration of the coupled model with both the “low‐top” (40 km, with limited chemistry) and “high‐top” (130 km, with comprehensive chemistry) versions of the atmospheric component. CESM2 contains many substantial science and infrastructure improvements and new capabilities since its previous major release, CESM1, resulting in improved historical simulations in comparison to CESM1 and available observations. These include major reductions in low‐latitude precipitation and shortwave cloud forcing biases; better representation of the Madden‐Julian Oscillation; better El Niño‐Southern Oscillation‐related teleconnections; and a global land carbon accumulation trend that agrees well with observationally based estimates. Most tropospheric and surface features of the low‐ and high‐top simulations are very similar to each other, so these improvements are present in both configurations. CESM2 has an equilibrium climate sensitivity of 5.1–5.3 °C, larger than in CESM1, primarily due to a combination of relatively small changes to cloud microphysics and boundary layer parameters. In contrast, CESM2's transient climate response of 1.9–2.0 °C is comparable to that of CESM1. The model outputs from these and many other simulations are available to the research community, and they represent CESM2's contributions to the Coupled Model Intercomparison Project Phase 6.